Perceived needs for the information communication technology (ICT)-based personalized health management program, and its association with information provision, health-related quality of life (HRQOL), and decisional conflict in cancer patients

Identification of the Needs and Preferences of Patients With Cancer for the Development of a Clinic App: Qualitative Study

BACKGROUND

Mobile health (mHealth) tools were developed during the past decades and are increasingly used by patients in cancer care too. Scientific research in the development of mHealth services is required in order to meet the various needs of patients and test usability.

OBJECTIVE

The aim of this study is to assess patients' needs, preferences, and usability of an app (My University Clinic [MUC] app) developed by the Comprehensive Cancer Center Freiburg (CCCF) Germany.

METHODS

Based on a qualitative cross-sectional approach, we conducted semistructured interviews with patients with cancer, addressing their needs, preferences, and usability of the designed MUC app. Patients treated by the CCCF were recruited based on a purposive sampling technique focusing on age, sex, cancer diagnoses, and treatment setting (inpatient, outpatient). Data analysis followed the qualitative content analysis according to Kuckartz and was performed using computer-assisted software (MAXQDA).

RESULTS

For the interviews, 17 patients with cancer were selected, covering a broad range of sampling parameters. The results showed that patients expect benefits in terms of improved information about the disease and communication with the clinic staff. Demands for additional features were identified (eg, a list of contact persons and medication management). The most important concerns referred to data security and the potential restriction of personal contacts with health care professionals of the clinical departments of the CCCF. In addition, some features for improving the design of the MUC app with respect to usability or for inclusion of interacting tools were suggested by the patients.

CONCLUSIONS

The results of this qualitative study were discussed within the multidisciplinary team and the MUC app providers. Patients' perspectives and needs will be included in further development of the MUC app. There will be a second study phase in which patients will receive a test version of the MUC app and will be asked about their experiences with it.

TRIAL REGISTRATION

Deutsches Register Klinischer Studien DRKS00022162; https://drks.de/search/de/trial/DRKS00022162.

Information Provision, Decision Self-efficacy, and Decisional Conflict in Adopting Health Behaviors Among Patients Treated for Colorectal Cancer: A Cross-sectional Study

BACKGROUND

Health promotion is necessary to mitigate the negative consequences of colorectal cancer and its treatment. Rates of behavior modification are low in populations of cancer patients. Studies are needed to determine the factors, such as decisional conflict, which influence adoption of healthy behaviors following a cancer diagnosis.

OBJECTIVE

To examine the effects of information provision, decision self-efficacy, and decisional conflict on the adoption of healthy behaviors among patients with colorectal cancer.

METHODS

This cross-sectional study focused on 251 patients with colorectal cancer in South Korea. Information provision, decision self-efficacy, and decisional conflict were measured using validated instruments. Patients rated their decisional conflict related to the adoption of behaviors that include regular exercise and a balanced diet.

RESULTS

Most participants (73%) reported low satisfaction with the amount of information received. Of the participants, 64% had low decision self-efficacy, and 80% experienced decisional conflict. The perception of a higher level of information provision was associated with greater decision self-efficacy (odds ratio, 4.63; 95% confidence interval, 1.61-13.35). Higher decision self-efficacy was associated with lower decisional conflict (odds ratio, 5.19; 95% confidence interval, 2.33-11.59).

CONCLUSION

Receiving adequate information is important for promoting patients' confidence in making decisions about their health and reducing decisional conflict in the adoption of healthy lifestyle changes following a cancer diagnosis.

IMPLICATION FOR PRACTICE

Oncology nurses should assess patient information needs and promote decision self-efficacy, thus empowering patients diagnosed with colorectal cancer to make lifestyle decisions that improve their health and quality of life.

A model to assess the impact of digital technologies on the health-related quality of life

OBJECTIVES

Health-related quality of life (HRQoL) is a vital instrument to account for individuals' well-being in various settings. However, no model of HRQoL allows for examining the effect of digital technology on HRQoL. Therefore, we extend an established HRQoL model by adding a digital technology-related construct. We refer to this extension as the technology-affected health-related quality of life (TA-HRQoL).

METHODS

We investigate the extended TA-HRQoL model through a survey. In the survey, we exemplify the use of digital technology through a device for self-managing bladder dysfunction. Hence, we explore whether the model extension proposed is valid and how determinants of the HRQoL affect patients with bladder dysfunction.

RESULTS

The results indicate that the use of digital technology improves the HRQoL. In our exemplary use scenario, the digital technology decreases bladder-related functional impairments and increases well-being and life satisfaction directly.

CONCLUSIONS

Our study may provide evidence for the influence of digital technologies on the HRQoL, thus supporting our model extension. We consider our proposed TA-HRQoL model as valid and as useful to account for the influence of digital technology on an individual's HRQoL. With the TA-HRQoL model, the impact of a digital technology on an individual's HRQoL can be assessed.

The major effects of health-related quality of life on 5-year survival prediction among lung cancer survivors: applications of machine learning

The primary goal of this study was to evaluate the major roles of health-related quality of life (HRQOL) in a 5-year lung cancer survival prediction model using machine learning techniques (MLTs). The predictive performances of the models were compared with data from 809 survivors who underwent lung cancer surgery. Each of the modeling technique was applied to two feature sets: feature set 1 included clinical and sociodemographic variables, and feature set 2 added HRQOL factors to the variables from feature set 1. One of each developed prediction model was trained with the decision tree (DT), logistic regression (LR), bagging, random forest (RF), and adaptive boosting (AdaBoost) methods, and then, the best algorithm for modeling was determined. The models' performances were compared using fivefold cross-validation. For feature set 1, there were no significant differences in model accuracies (ranging from 0.647 to 0.713). Among the models in feature set 2, the AdaBoost and RF models outperformed the other prognostic models [area under the curve (AUC) = 0.850, 0.898, 0.981, 0.966, and 0.949 for the DT, LR, bagging, RF and AdaBoost models, respectively] in the test set. Overall, 5-year disease-free lung cancer survival prediction models with MLTs that included HRQOL as well as clinical variables improved predictive performance.

Effectiveness of a Smartphone Application as a Support Tool for Patients Undergoing Breast Cancer Chemotherapy: A Randomized Controlled Trial

BACKGROUND

Outpatients undergoing cancer chemotherapy experience anxiety related to adverse drug reactions that they can experience at home. We developed a breast cancer patient support system (BPSS) application (app). The BPSS app chronologically and quantitatively records patients' subjective and objective symptoms during breast cancer chemotherapy, with the goal of providing supportive management for adverse drug reactions. The present study examined whether the BPSS app is an effective tool for supporting patients undergoing chemotherapy.

PATIENTS AND METHODS

A total of 102 patients undergoing chemotherapy at the Showa University Hospital (Tokyo, Japan) were enrolled in the present order- and age-controlled clinical trial and randomized into BPSS or no-BPSS app groups. The patients underwent 4 courses of chemotherapy. The primary outcome was the change in the hospital anxiety and depression scale score, which was assessed directly before and after the 4 courses of chemotherapy. Other outcomes included health literacy (measured using the 14-item health literacy scale (HLS-14), side effects, and app adherence.

RESULTS

Of the 102 patients, 95 completed the present study. No significant improvement was seen in anxiety, depression, or health literacy at the end of treatment between the BPSS and no-BPSS app groups. Overall, 1868 side effects were reported. When the patients' records were compared with the medical staff records, the analysis revealed that the medical staff had underestimated some grade 3 symptoms.

CONCLUSION

The BPSS app is a feasible tool for patients with breast cancer and might be useful as a support tool for information sharing between patients and medical staff in an effort to optimize chemotherapy and deliver suitable patient care and support.

Study of the uses of Information and Communication Technologies by Pain Treatment Unit Physicians

Adequate use of Information and Communication Technologies (ICTs) in health has been shown to save the patient and caregiver time, improve access to the health system, improve diagnosis and control of disease or treatment. All this results in cost savings, and more importantly, they help improve the quality of service and the lives of patients. The purpose of this study is to analyse the differences in the uses of this ICTs between those physicians that belong to Pain Treatment Units (PU) and other physicians that work in pain not linked to these PUs. An online survey, generated by Netquest online survey tool, was sent to both groups of professionals and the data collected was statistical analysed through a logistic regression methodology which is the Logit binomial model. Our results show that those physicians that belong to PUs use ICTs more frequently and consider it more relevant to their clinical practice.